As a distributed column storage database, a KeyValue type distributed database has high scalability and robustness, and has been widely applied in more and more systems. A user table of the KeyValue type distributed database is generally designed to store data that is in a relatively simple data format, has simple correlation, but may be massive in amount, for example, to store web page address information, to store call record information, or to store network access record information, and the like. The KeyValue type distributed database can provide fast query according to a RowKey of a data record, and the fast query is irrelevant to a data amount. A physical node can be dynamically added for the KeyValue type distributed database when a current storage space usage reaches a threshold.
In existing database applications of enterprises, generally many user data tables are correlated, these data tables have different sizes, and an internal correlation may exist between data of tables. However, the KeyValue type distributed database based on a sparse matrix is suitable to store a table with a large amount of data. If these original tables are directly imported into the KeyValue type distributed database, excessive small tables exist; therefore, it is difficult to implement cross-table correlated query, and management complexity also increases. That is, when data in conventional applications is migrated into the KeyValue type distributed database, to complete correlation query between one user table and another user table, different tables need to be queried, and constant data locating needs to be performed, causing low efficiency.